Pandas Profiling Report

Dataset statistics

Number of variables	35
Number of observations	468
Missing cells	6276
Missing cells (%)	38.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	128.1 KiB
Average record size in memory	280.3 B

Variable types

Numeric	12
Categorical	23

Warnings

`Name English` has a high cardinality: 284 distinct values	High cardinality
`Position` has a high cardinality: 135 distinct values	High cardinality
`Ban_Total` is highly correlated with `Ban_G.P.` and 15 other fields	High correlation
`Ban_G.P.` is highly correlated with `Ban_Total` and 12 other fields	High correlation
`Eng_Total` is highly correlated with `Ban_Total` and 11 other fields	High correlation
`Eng_G.P.` is highly correlated with `Ban_Total` and 8 other fields	High correlation
`Phy_Total` is highly correlated with `Ban_Total` and 14 other fields	High correlation
`Phy_G.P.` is highly correlated with `Ban_Total` and 14 other fields	High correlation
`Che_Total` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`Che_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`BIO_Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`BIO_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`Math_Total` is highly correlated with `Ban_Total` and 14 other fields	High correlation
`Math_G.P.` is highly correlated with `Phy_Total` and 12 other fields	High correlation
`ICT_Total` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`ICt_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`APT` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`APT_G.P.` is highly correlated with `Phy_Total` and 10 other fields	High correlation
`Grand Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`TTL_GP` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`No.s of F` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`Ban_Total` is highly correlated with `Ban_G.P.` and 16 other fields	High correlation
`Ban_G.P.` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`Eng_Total` is highly correlated with `Ban_Total` and 11 other fields	High correlation
`Eng_G.P.` is highly correlated with `Ban_Total` and 8 other fields	High correlation
`Phy_Total` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`Phy_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`Che_Total` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`Che_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`BIO_Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`BIO_G.P.` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`Math_Total` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`Math_G.P.` is highly correlated with `Phy_Total` and 13 other fields	High correlation
`ICT_Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`ICt_G.P.` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`APT` is highly correlated with `Ban_Total` and 16 other fields	High correlation
`APT_G.P.` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`Grand Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`TTL_GP` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`No.s of F` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`Ban_Total` is highly correlated with `Ban_G.P.` and 5 other fields	High correlation
`Ban_G.P.` is highly correlated with `Ban_Total` and 7 other fields	High correlation
`Eng_Total` is highly correlated with `Eng_G.P.` and 3 other fields	High correlation
`Eng_G.P.` is highly correlated with `Eng_Total` and 3 other fields	High correlation
`Phy_Total` is highly correlated with `Phy_G.P.` and 13 other fields	High correlation
`Phy_G.P.` is highly correlated with `Phy_Total` and 13 other fields	High correlation
`Che_Total` is highly correlated with `Phy_Total` and 11 other fields	High correlation
`Che_G.P.` is highly correlated with `Phy_Total` and 12 other fields	High correlation
`BIO_Total` is highly correlated with `Ban_Total` and 11 other fields	High correlation
`BIO_G.P.` is highly correlated with `Ban_Total` and 13 other fields	High correlation
`Math_Total` is highly correlated with `Phy_Total` and 9 other fields	High correlation
`Math_G.P.` is highly correlated with `Phy_Total` and 6 other fields	High correlation
`ICT_Total` is highly correlated with `Ban_G.P.` and 10 other fields	High correlation
`ICt_G.P.` is highly correlated with `Ban_G.P.` and 11 other fields	High correlation
`APT` is highly correlated with `Phy_Total` and 6 other fields	High correlation
`APT_G.P.` is highly correlated with `Phy_Total` and 5 other fields	High correlation
`Grand Total` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`TTL_GP` is highly correlated with `Ban_Total` and 17 other fields	High correlation
`No.s of F` is highly correlated with `Ban_Total` and 15 other fields	High correlation
`ATP_Position` is highly correlated with `Che_G.P.` and 20 other fields	High correlation
`Che_G.P.` is highly correlated with `ATP_Position` and 22 other fields	High correlation
`Eng_G.P.` is highly correlated with `ATP_Position` and 15 other fields	High correlation
`Section` is highly correlated with `Ban_G.P.` and 2 other fields	High correlation
`APT_L.G.` is highly correlated with `ATP_Position` and 12 other fields	High correlation
`BIO_Total` is highly correlated with `Che_G.P.` and 25 other fields	High correlation
`Math_G.P.` is highly correlated with `ATP_Position` and 18 other fields	High correlation
`Ban_G.P.` is highly correlated with `ATP_Position` and 22 other fields	High correlation
`TTL_GP` is highly correlated with `ATP_Position` and 25 other fields	High correlation
`APT_G.P.` is highly correlated with `ATP_Position` and 12 other fields	High correlation
`Phy_G.P.` is highly correlated with `ATP_Position` and 20 other fields	High correlation
`Eng_Total` is highly correlated with `Che_G.P.` and 17 other fields	High correlation
`Sec_Position` is highly correlated with `ATP_Position` and 24 other fields	High correlation
`ICT_L.G.` is highly correlated with `Che_G.P.` and 21 other fields	High correlation
`Math_Total` is highly correlated with `ATP_Position` and 26 other fields	High correlation
`4th Sub` is highly correlated with `Section` and 2 other fields	High correlation
`Che_L.G.` is highly correlated with `ATP_Position` and 21 other fields	High correlation
`Ban_Total` is highly correlated with `ATP_Position` and 23 other fields	High correlation
`Che_Total` is highly correlated with `Che_G.P.` and 25 other fields	High correlation
`ICt_G.P.` is highly correlated with `Che_G.P.` and 21 other fields	High correlation
`ID No.` is highly correlated with `Section` and 1 other fields	High correlation
`ICT_Total` is highly correlated with `ATP_Position` and 26 other fields	High correlation
`APT` is highly correlated with `ATP_Position` and 21 other fields	High correlation
`Grand Total` is highly correlated with `ATP_Position` and 28 other fields	High correlation
`TTL_L.G.` is highly correlated with `ATP_Position` and 26 other fields	High correlation
`BIO_G.P.` is highly correlated with `ATP_Position` and 23 other fields	High correlation
`Phy_L.G.` is highly correlated with `ATP_Position` and 24 other fields	High correlation
`Ban_L.G.` is highly correlated with `ATP_Position` and 21 other fields	High correlation
`Phy_Total` is highly correlated with `ATP_Position` and 24 other fields	High correlation
`Math_L.G.` is highly correlated with `ATP_Position` and 22 other fields	High correlation
`BIO_L.G.` is highly correlated with `BIO_Total` and 22 other fields	High correlation
`Eng_L.G.` is highly correlated with `Eng_G.P.` and 12 other fields	High correlation
`No.s of F` is highly correlated with `Che_G.P.` and 20 other fields	High correlation
`ATP_Position` is highly correlated with `APT_L.G.` and 1 other fields	High correlation
`Che_G.P.` is highly correlated with `Che_L.G.`	High correlation
`Eng_G.P.` is highly correlated with `Eng_L.G.`	High correlation
`Section` is highly correlated with `4th Sub`	High correlation
`APT_L.G.` is highly correlated with `ATP_Position` and 1 other fields	High correlation
`Math_G.P.` is highly correlated with `TTL_L.G.` and 1 other fields	High correlation
`Ban_G.P.` is highly correlated with `Ban_L.G.`	High correlation
`APT_G.P.` is highly correlated with `ATP_Position` and 1 other fields	High correlation
`Phy_G.P.` is highly correlated with `Phy_L.G.`	High correlation
`Sec_Position` is highly correlated with `TTL_L.G.`	High correlation
`ICT_L.G.` is highly correlated with `ICt_G.P.` and 1 other fields	High correlation
`4th Sub` is highly correlated with `Section`	High correlation
`Che_L.G.` is highly correlated with `Che_G.P.`	High correlation
`ICt_G.P.` is highly correlated with `ICT_L.G.`	High correlation
`TTL_L.G.` is highly correlated with `Math_G.P.` and 2 other fields	High correlation
`BIO_G.P.` is highly correlated with `BIO_L.G.`	High correlation
`Phy_L.G.` is highly correlated with `Phy_G.P.`	High correlation
`Ban_L.G.` is highly correlated with `Ban_G.P.`	High correlation
`Math_L.G.` is highly correlated with `Math_G.P.` and 1 other fields	High correlation
`BIO_L.G.` is highly correlated with `ICT_L.G.` and 1 other fields	High correlation
`Eng_L.G.` is highly correlated with `Eng_G.P.`	High correlation
`ID No.` has 179 (38.2%) missing values	Missing
`Name English` has 183 (39.1%) missing values	Missing
`Section` has 179 (38.2%) missing values	Missing
`4th Sub` has 179 (38.2%) missing values	Missing
`Ban_Total` has 179 (38.2%) missing values	Missing
`Ban_G.P.` has 179 (38.2%) missing values	Missing
`Ban_L.G.` has 179 (38.2%) missing values	Missing
`Eng_Total` has 179 (38.2%) missing values	Missing
`Eng_G.P.` has 179 (38.2%) missing values	Missing
`Eng_L.G.` has 179 (38.2%) missing values	Missing
`Phy_Total` has 179 (38.2%) missing values	Missing
`Phy_G.P.` has 179 (38.2%) missing values	Missing
`Phy_L.G.` has 179 (38.2%) missing values	Missing
`Che_Total` has 179 (38.2%) missing values	Missing
`Che_G.P.` has 179 (38.2%) missing values	Missing
`Che_L.G.` has 179 (38.2%) missing values	Missing
`BIO_Total` has 179 (38.2%) missing values	Missing
`BIO_G.P.` has 179 (38.2%) missing values	Missing
`BIO_L.G.` has 179 (38.2%) missing values	Missing
`Math_Total` has 179 (38.2%) missing values	Missing
`Math_G.P.` has 179 (38.2%) missing values	Missing
`Math_L.G.` has 179 (38.2%) missing values	Missing
`ICT_Total` has 179 (38.2%) missing values	Missing
`ICt_G.P.` has 179 (38.2%) missing values	Missing
`ICT_L.G.` has 179 (38.2%) missing values	Missing
`APT` has 186 (39.7%) missing values	Missing
`APT_G.P.` has 179 (38.2%) missing values	Missing
`APT_L.G.` has 179 (38.2%) missing values	Missing
`Grand Total` has 179 (38.2%) missing values	Missing
`TTL_GP` has 179 (38.2%) missing values	Missing
`TTL_L.G.` has 179 (38.2%) missing values	Missing
`No.s of F` has 179 (38.2%) missing values	Missing
`Sec_Position` has 179 (38.2%) missing values	Missing
`Position` has 179 (38.2%) missing values	Missing
`ATP_Position` has 179 (38.2%) missing values	Missing
`Name English` is uniformly distributed	Uniform
`TTL_GP` has 153 (32.7%) zeros	Zeros
`No.s of F` has 136 (29.1%) zeros	Zeros

Reproduction

Analysis started	2021-07-04 14:12:40.387762
Analysis finished	2021-07-04 14:13:05.048096
Duration	24.66 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

ID No.
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	289
Distinct (%)	100.0%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	1297390.201

Minimum	1190001
Maximum	2190033
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	1190001
5-th percentile	1190016.4
Q1	1190079
median	1190152
Q3	1190227
95-th percentile	2190017.6
Maximum	2190033
Range	1000032
Interquartile range (IQR)	148

Descriptive statistics

Standard deviation	309951.3797
Coefficient of variation (CV)	0.2389037465
Kurtosis	4.541619574
Mean	1297390.201
Median Absolute Deviation (MAD)	74
Skewness	2.551516488
Sum	374945768
Variance	9.606985775 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2190010	1	0.2%
1190067	1	0.2%
1190213	1	0.2%
1190165	1	0.2%
1190232	1	0.2%
1190037	1	0.2%
1190022	1	0.2%
1190243	1	0.2%
1190084	1	0.2%
2190032	1	0.2%
Other values (279)	279	59.6%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1190001	1	0.2%
1190002	1	0.2%
1190003	1	0.2%
1190004	1	0.2%
1190005	1	0.2%
1190006	1	0.2%
1190007	1	0.2%
1190008	1	0.2%
1190009	1	0.2%
1190010	1	0.2%

Value	Count	Frequency (%)
2190033	1	0.2%
2190032	1	0.2%
2190031	1	0.2%
2190030	1	0.2%
2190029	1	0.2%
2190028	1	0.2%
2190027	1	0.2%
2190026	1	0.2%
2190025	1	0.2%
2190023	1	0.2%

Name English
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	284
Distinct (%)	99.6%
Missing	183
Missing (%)	39.1%
Memory size	3.8 KiB

SHOBNOM SABIHA	2
BADHON ROY	1
RAJOWONE SHARIAR	1
RABBI ISLAM JOY	1
MUBTASIM FUAD	1
Other values (279)	279

Length

Max length	28
Median length	17
Mean length	17.16842105
Min length	5

Characters and Unicode

Total characters	4893
Distinct characters	48
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	283 ?
Unique (%)	99.3%

Sample

1st row	SAIMA SHARMIN MONISHA
2nd row	MOSSAMAT NUSAIBA ISLAM
3rd row	TAHMINA AFROJ RITU
4th row	ANUPOMA DEBSHARMA
5th row	MARIA AKTER MIM

Common Values

Value	Count	Frequency (%)
SHOBNOM SABIHA	2	0.4%
BADHON ROY	1	0.2%
RAJOWONE SHARIAR	1	0.2%
RABBI ISLAM JOY	1	0.2%
MUBTASIM FUAD	1	0.2%
MUSFEKA IFFAT SENIN	1	0.2%
MD. MARUF HASAN MUNNA	1	0.2%
MD. NUR ISTYAK LIKHAN	1	0.2%
FARHAT MUBASSHIRA	1	0.2%
KAMLESH ROY	1	0.2%
Other values (274)	274	58.5%
(Missing)	183	39.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
md	100	12.0%
islam	20	2.4%
roy	14	1.7%
akter	14	1.7%
hasan	14	1.7%
mst	11	1.3%
rahman	11	1.3%
most	10	1.2%
tasnim	7	0.8%
al	7	0.8%
Other values (521)	626	75.1%

Most occurring characters

Value	Count	Frequency (%)
A	806	16.5%
	549	11.2%
M	373	7.6%
I	346	7.1%
S	309	6.3%
R	274	5.6%
H	261	5.3%
N	261	5.3%
D	210	4.3%
T	178	3.6%
Other values (38)	1326	27.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4107	83.9%
Space Separator	549	11.2%
Other Punctuation	127	2.6%
Lowercase Letter	106	2.2%
Dash Punctuation	4	0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	806	19.6%
M	373	9.1%
I	346	8.4%
S	309	7.5%
R	274	6.7%
H	261	6.4%
N	261	6.4%
D	210	5.1%
T	178	4.3%
U	174	4.2%
Other values (15)	915	22.3%

Lowercase Letter

Value	Count	Frequency (%)
a	17	16.0%
i	10	9.4%
s	8	7.5%
l	7	6.6%
n	7	6.6%
r	7	6.6%
h	7	6.6%
u	6	5.7%
o	6	5.7%
d	5	4.7%
Other values (10)	26	24.5%

Space Separator

Value	Count	Frequency (%)
	549	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	127	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4213	86.1%
Common	680	13.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	806	19.1%
M	373	8.9%
I	346	8.2%
S	309	7.3%
R	274	6.5%
H	261	6.2%
N	261	6.2%
D	210	5.0%
T	178	4.2%
U	174	4.1%
Other values (35)	1021	24.2%

Common

Value	Count	Frequency (%)
	549	80.7%
.	127	18.7%
-	4	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4893	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	806	16.5%
	549	11.2%
M	373	7.6%
I	346	7.1%
S	309	6.3%
R	274	5.6%
H	261	5.3%
N	261	5.3%
D	210	4.3%
T	178	3.6%
Other values (38)	1326	27.1%

Section
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	10
Distinct (%)	3.5%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

Jagori	35
Nirjor	34
Muktodhara	33
Chayatoru	32
Sarnokamal	32
Other values (5)	123

Length

Max length	11
Median length	9
Mean length	8.529411765
Min length	6

Characters and Unicode

Total characters	2465
Distinct characters	25
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Shankhamala
2nd row	Shankhamala
3rd row	Shankhamala
4th row	Shankhamala
5th row	Shankhamala

Common Values

Value	Count	Frequency (%)
Jagori	35	7.5%
Nirjor	34	7.3%
Muktodhara	33	7.1%
Chayatoru	32	6.8%
Sarnokamal	32	6.8%
Dhanshiri	32	6.8%
Chayanot	30	6.4%
Chayabithi	30	6.4%
Shankhamala	17	3.6%
Tapobon	14	3.0%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
jagori	35	12.1%
nirjor	34	11.8%
muktodhara	33	11.4%
sarnokamal	32	11.1%
chayatoru	32	11.1%
dhanshiri	32	11.1%
chayabithi	30	10.4%
chayanot	30	10.4%
shankhamala	17	5.9%
tapobon	14	4.8%

Most occurring characters

Value	Count	Frequency (%)
a	495	20.1%
h	253	10.3%
r	232	9.4%
o	224	9.1%
i	193	7.8%
n	125	5.1%
t	125	5.1%
C	92	3.7%
y	92	3.7%
k	82	3.3%
Other values (15)	552	22.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2176	88.3%
Uppercase Letter	289	11.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	495	22.7%
h	253	11.6%
r	232	10.7%
o	224	10.3%
i	193	8.9%
n	125	5.7%
t	125	5.7%
y	92	4.2%
k	82	3.8%
u	65	3.0%
Other values (8)	290	13.3%

Uppercase Letter

Value	Count	Frequency (%)
C	92	31.8%
S	49	17.0%
J	35	12.1%
N	34	11.8%
M	33	11.4%
D	32	11.1%
T	14	4.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2465	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	495	20.1%
h	253	10.3%
r	232	9.4%
o	224	9.1%
i	193	7.8%
n	125	5.1%
t	125	5.1%
C	92	3.7%
y	92	3.7%
k	82	3.3%
Other values (15)	552	22.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2465	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	495	20.1%
h	253	10.3%
r	232	9.4%
o	224	9.1%
i	193	7.8%
n	125	5.1%
t	125	5.1%
C	92	3.7%
y	92	3.7%
k	82	3.3%
Other values (15)	552	22.4%

4th Sub
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	1.0%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

Math	178
Bio	80
Agri	31

Length

Max length	4
Median length	4
Mean length	3.723183391
Min length	3

Characters and Unicode

Total characters	1076
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Agri
2nd row	Agri
3rd row	Agri
4th row	Agri
5th row	Agri

Common Values

Value	Count	Frequency (%)
Math	178	38.0%
Bio	80	17.1%
Agri	31	6.6%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
math	178	61.6%
bio	80	27.7%
agri	31	10.7%

Most occurring characters

Value	Count	Frequency (%)
M	178	16.5%
a	178	16.5%
t	178	16.5%
h	178	16.5%
i	111	10.3%
B	80	7.4%
o	80	7.4%
A	31	2.9%
g	31	2.9%
r	31	2.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	787	73.1%
Uppercase Letter	289	26.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	178	22.6%
t	178	22.6%
h	178	22.6%
i	111	14.1%
o	80	10.2%
g	31	3.9%
r	31	3.9%

Uppercase Letter

Value	Count	Frequency (%)
M	178	61.6%
B	80	27.7%
A	31	10.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1076	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
M	178	16.5%
a	178	16.5%
t	178	16.5%
h	178	16.5%
i	111	10.3%
B	80	7.4%
o	80	7.4%
A	31	2.9%
g	31	2.9%
r	31	2.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1076	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
M	178	16.5%
a	178	16.5%
t	178	16.5%
h	178	16.5%
i	111	10.3%
B	80	7.4%
o	80	7.4%
A	31	2.9%
g	31	2.9%
r	31	2.9%

Ban_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	61
Distinct (%)	21.1%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	62.06228374

Minimum	0
Maximum	91
Zeros	1
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	35
Q1	53
median	64
Q3	73
95-th percentile	82.6
Maximum	91
Range	91
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	14.51494427
Coefficient of variation (CV)	0.233877057
Kurtosis	0.6413349415
Mean	62.06228374
Median Absolute Deviation (MAD)	10
Skewness	-0.6441647735
Sum	17936
Variance	210.6836073
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
64	20	4.3%
67	12	2.6%
62	12	2.6%
56	11	2.4%
69	10	2.1%
75	9	1.9%
68	8	1.7%
49	8	1.7%
65	8	1.7%
79	7	1.5%
Other values (51)	184	39.3%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.2%
22	2	0.4%
26	1	0.2%
27	1	0.2%
29	2	0.4%
31	1	0.2%
33	2	0.4%
34	3	0.6%
35	3	0.6%
36	3	0.6%

Value	Count	Frequency (%)
91	1	0.2%
90	1	0.2%
89	2	0.4%
88	1	0.2%
86	1	0.2%
85	4	0.9%
84	3	0.6%
83	2	0.4%
82	6	1.3%
81	1	0.2%

Ban_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

3.5	83
4.0	66
3.0	60
0.0	46
5.0	34

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	4.0
3rd row	4.0
4th row	3.0
5th row	3.5

Common Values

Value	Count	Frequency (%)
3.5	83	17.7%
4.0	66	14.1%
3.0	60	12.8%
0.0	46	9.8%
5.0	34	7.3%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.5	83	28.7%
4.0	66	22.8%
3.0	60	20.8%
0.0	46	15.9%
5.0	34	11.8%

Most occurring characters

Value	Count	Frequency (%)
.	289	33.3%
0	252	29.1%
3	143	16.5%
5	117	13.5%
4	66	7.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	252	43.6%
3	143	24.7%
5	117	20.2%
4	66	11.4%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	289	33.3%
0	252	29.1%
3	143	16.5%
5	117	13.5%
4	66	7.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	289	33.3%
0	252	29.1%
3	143	16.5%
5	117	13.5%
4	66	7.6%

Ban_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

A-	83
A	66
B	60
F	43
A+	34

Length

Max length	3
Median length	1
Mean length	1.425605536
Min length	1

Characters and Unicode

Total characters	412
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	A
3rd row	A
4th row	B
5th row	A-

Common Values

Value	Count	Frequency (%)
A-	83	17.7%
A	66	14.1%
B	60	12.8%
F	43	9.2%
A+	34	7.3%
ABS	3	0.6%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	183	63.3%
b	60	20.8%
f	43	14.9%
abs	3	1.0%

Most occurring characters

Value	Count	Frequency (%)
A	186	45.1%
-	83	20.1%
B	63	15.3%
F	43	10.4%
+	34	8.3%
S	3	0.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	295	71.6%
Dash Punctuation	83	20.1%
Math Symbol	34	8.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	186	63.1%
B	63	21.4%
F	43	14.6%
S	3	1.0%

Dash Punctuation

Value	Count	Frequency (%)
-	83	100.0%

Math Symbol

Value	Count	Frequency (%)
+	34	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	295	71.6%
Common	117	28.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	186	63.1%
B	63	21.4%
F	43	14.6%
S	3	1.0%

Common

Value	Count	Frequency (%)
-	83	70.9%
+	34	29.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	412	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	186	45.1%
-	83	20.1%
B	63	15.3%
F	43	10.4%
+	34	8.3%
S	3	0.7%

Eng_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	65
Distinct (%)	22.5%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	54.42214533

Minimum	0
Maximum	88
Zeros	1
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	27.4
Q1	46
median	57
Q3	65
95-th percentile	76
Maximum	88
Range	88
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	15.44260186
Coefficient of variation (CV)	0.2837558455
Kurtosis	0.61201958
Mean	54.42214533
Median Absolute Deviation (MAD)	9
Skewness	-0.6541760136
Sum	15728
Variance	238.4739523
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
49	15	3.2%
54	12	2.6%
60	11	2.4%
62	10	2.1%
59	10	2.1%
58	9	1.9%
57	9	1.9%
65	9	1.9%
63	8	1.7%
51	8	1.7%
Other values (55)	188	40.2%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.2%
7	1	0.2%
10	1	0.2%
12	1	0.2%
13	2	0.4%
16	1	0.2%
19	2	0.4%
20	2	0.4%
22	1	0.2%
24	1	0.2%

Value	Count	Frequency (%)
88	1	0.2%
87	2	0.4%
84	2	0.4%
82	2	0.4%
80	4	0.9%
79	2	0.4%
76	4	0.9%
75	1	0.2%
74	2	0.4%
73	5	1.1%

Eng_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

3.0	81
0.0	80
3.5	78
4.0	37
5.0	13

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	3.0
3rd row	3.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
3.0	81	17.3%
0.0	80	17.1%
3.5	78	16.7%
4.0	37	7.9%
5.0	13	2.8%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3.0	81	28.0%
0.0	80	27.7%
3.5	78	27.0%
4.0	37	12.8%
5.0	13	4.5%

Most occurring characters

Value	Count	Frequency (%)
0	291	33.6%
.	289	33.3%
3	159	18.3%
5	91	10.5%
4	37	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	291	50.3%
3	159	27.5%
5	91	15.7%
4	37	6.4%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	291	33.6%
.	289	33.3%
3	159	18.3%
5	91	10.5%
4	37	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	291	33.6%
.	289	33.3%
3	159	18.3%
5	91	10.5%
4	37	4.3%

Eng_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

B	81
A-	78
F	77
A	37
A+	13

Length

Max length	3
Median length	1
Mean length	1.335640138
Min length	1

Characters and Unicode

Total characters	386
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	B
3rd row	B
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
B	81	17.3%
A-	78	16.7%
F	77	16.5%
A	37	7.9%
A+	13	2.8%
ABS	3	0.6%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	128	44.3%
b	81	28.0%
f	77	26.6%
abs	3	1.0%

Most occurring characters

Value	Count	Frequency (%)
A	131	33.9%
B	84	21.8%
-	78	20.2%
F	77	19.9%
+	13	3.4%
S	3	0.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	295	76.4%
Dash Punctuation	78	20.2%
Math Symbol	13	3.4%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	131	44.4%
B	84	28.5%
F	77	26.1%
S	3	1.0%

Dash Punctuation

Value	Count	Frequency (%)
-	78	100.0%

Math Symbol

Value	Count	Frequency (%)
+	13	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	295	76.4%
Common	91	23.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	131	44.4%
B	84	28.5%
F	77	26.1%
S	3	1.0%

Common

Value	Count	Frequency (%)
-	78	85.7%
+	13	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	386	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	131	33.9%
B	84	21.8%
-	78	20.2%
F	77	19.9%
+	13	3.4%
S	3	0.8%

Phy_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	76
Distinct (%)	26.3%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	59.20069204

Minimum	8
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	8
5-th percentile	26
Q1	44
median	59
Q3	76
95-th percentile	91.6
Maximum	100
Range	92
Interquartile range (IQR)	32

Descriptive statistics

Standard deviation	20.27984425
Coefficient of variation (CV)	0.3425609322
Kurtosis	-0.781296891
Mean	59.20069204
Median Absolute Deviation (MAD)	16
Skewness	-0.1244528344
Sum	17109
Variance	411.2720829
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
57	10	2.1%
49	9	1.9%
44	8	1.7%
79	7	1.5%
76	7	1.5%
50	7	1.5%
68	7	1.5%
58	6	1.3%
64	6	1.3%
60	6	1.3%
Other values (66)	216	46.2%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
8	1	0.2%
10	1	0.2%
18	3	0.6%
20	1	0.2%
22	1	0.2%
23	3	0.6%
24	2	0.4%
26	4	0.9%
27	4	0.9%
28	4	0.9%

Value	Count	Frequency (%)
100	1	0.2%
97	2	0.4%
95	2	0.4%
94	3	0.6%
93	4	0.9%
92	3	0.6%
91	3	0.6%
90	4	0.9%
88	5	1.1%
87	4	0.9%

Phy_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

0.0	85
5.0	60
3.0	57
3.5	47
4.0	40

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5.0
2nd row	4.0
3rd row	5.0
4th row	3.5
5th row	5.0

Common Values

Value	Count	Frequency (%)
0.0	85	18.2%
5.0	60	12.8%
3.0	57	12.2%
3.5	47	10.0%
4.0	40	8.5%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	85	29.4%
5.0	60	20.8%
3.0	57	19.7%
3.5	47	16.3%
4.0	40	13.8%

Most occurring characters

Value	Count	Frequency (%)
0	327	37.7%
.	289	33.3%
5	107	12.3%
3	104	12.0%
4	40	4.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	327	56.6%
5	107	18.5%
3	104	18.0%
4	40	6.9%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	327	37.7%
.	289	33.3%
5	107	12.3%
3	104	12.0%
4	40	4.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	327	37.7%
.	289	33.3%
5	107	12.3%
3	104	12.0%
4	40	4.6%

Phy_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	75
A+	60
B	56
A-	47
A	40

Length

Max length	3
Median length	1
Mean length	1.446366782
Min length	1

Characters and Unicode

Total characters	418
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A+
2nd row	A
3rd row	A+
4th row	A-
5th row	A+

Common Values

Value	Count	Frequency (%)
F	75	16.0%
A+	60	12.8%
B	56	12.0%
A-	47	10.0%
A	40	8.5%
ABS	11	2.4%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	147	50.9%
f	75	26.0%
b	56	19.4%
abs	11	3.8%

Most occurring characters

Value	Count	Frequency (%)
A	158	37.8%
F	75	17.9%
B	67	16.0%
+	60	14.4%
-	47	11.2%
S	11	2.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	311	74.4%
Math Symbol	60	14.4%
Dash Punctuation	47	11.2%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	158	50.8%
F	75	24.1%
B	67	21.5%
S	11	3.5%

Math Symbol

Value	Count	Frequency (%)
+	60	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	47	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	311	74.4%
Common	107	25.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	158	50.8%
F	75	24.1%
B	67	21.5%
S	11	3.5%

Common

Value	Count	Frequency (%)
+	60	56.1%
-	47	43.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	418	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	158	37.8%
F	75	17.9%
B	67	16.0%
+	60	14.4%
-	47	11.2%
S	11	2.6%

Che_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	73
Distinct (%)	25.3%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	57.5017301

Minimum	6
Maximum	91
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	6
5-th percentile	24
Q1	46
median	58
Q3	72
95-th percentile	84
Maximum	91
Range	85
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	18.218604
Coefficient of variation (CV)	0.3168357538
Kurtosis	-0.2519957962
Mean	57.5017301
Median Absolute Deviation (MAD)	13
Skewness	-0.4102630609
Sum	16618
Variance	331.9175317
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
55	11	2.4%
50	10	2.1%
73	10	2.1%
65	9	1.9%
49	9	1.9%
46	8	1.7%
68	8	1.7%
58	8	1.7%
59	7	1.5%
56	7	1.5%
Other values (63)	202	43.2%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6	2	0.4%
12	1	0.2%
13	1	0.2%
15	1	0.2%
16	2	0.4%
17	1	0.2%
19	2	0.4%
20	1	0.2%
21	2	0.4%
23	1	0.2%

Value	Count	Frequency (%)
91	3	0.6%
90	3	0.6%
89	2	0.4%
88	2	0.4%
87	2	0.4%
85	1	0.2%
84	3	0.6%
83	2	0.4%
82	3	0.6%
81	6	1.3%

Che_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

0.0	79
3.0	68
3.5	56
4.0	48
5.0	38

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5.0
2nd row	3.5
3rd row	4.0
4th row	0.0
5th row	3.5

Common Values

Value	Count	Frequency (%)
0.0	79	16.9%
3.0	68	14.5%
3.5	56	12.0%
4.0	48	10.3%
5.0	38	8.1%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	79	27.3%
3.0	68	23.5%
3.5	56	19.4%
4.0	48	16.6%
5.0	38	13.1%

Most occurring characters

Value	Count	Frequency (%)
0	312	36.0%
.	289	33.3%
3	124	14.3%
5	94	10.8%
4	48	5.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	312	54.0%
3	124	21.5%
5	94	16.3%
4	48	8.3%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	312	36.0%
.	289	33.3%
3	124	14.3%
5	94	10.8%
4	48	5.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	312	36.0%
.	289	33.3%
3	124	14.3%
5	94	10.8%
4	48	5.5%

Che_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	72
B	68
A-	56
A	48
A+	38

Length

Max length	3
Median length	1
Mean length	1.373702422
Min length	1

Characters and Unicode

Total characters	397
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A+
2nd row	A-
3rd row	A
4th row	F
5th row	A-

Common Values

Value	Count	Frequency (%)
F	72	15.4%
B	68	14.5%
A-	56	12.0%
A	48	10.3%
A+	38	8.1%
ABS	7	1.5%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	142	49.1%
f	72	24.9%
b	68	23.5%
abs	7	2.4%

Most occurring characters

Value	Count	Frequency (%)
A	149	37.5%
B	75	18.9%
F	72	18.1%
-	56	14.1%
+	38	9.6%
S	7	1.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	303	76.3%
Dash Punctuation	56	14.1%
Math Symbol	38	9.6%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	149	49.2%
B	75	24.8%
F	72	23.8%
S	7	2.3%

Math Symbol

Value	Count	Frequency (%)
+	38	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	56	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	303	76.3%
Common	94	23.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	149	49.2%
B	75	24.8%
F	72	23.8%
S	7	2.3%

Common

Value	Count	Frequency (%)
-	56	59.6%
+	38	40.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	397	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	149	37.5%
B	75	18.9%
F	72	18.1%
-	56	14.1%
+	38	9.6%
S	7	1.8%

BIO_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	75
Distinct (%)	26.0%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	60.43944637

Minimum	0
Maximum	95
Zeros	1
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	28.2
Q1	49
median	62
Q3	75
95-th percentile	89
Maximum	95
Range	95
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	18.75825654
Coefficient of variation (CV)	0.3103644668
Kurtosis	-0.3891189436
Mean	60.43944637
Median Absolute Deviation (MAD)	13
Skewness	-0.3849784584
Sum	17467
Variance	351.8721886
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
49	14	3.0%
61	11	2.4%
71	10	2.1%
73	10	2.1%
76	9	1.9%
65	8	1.7%
77	7	1.5%
50	7	1.5%
79	7	1.5%
36	7	1.5%
Other values (65)	199	42.5%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.2%
14	1	0.2%
16	1	0.2%
17	1	0.2%
18	2	0.4%
19	1	0.2%
21	1	0.2%
22	2	0.4%
23	2	0.4%
25	1	0.2%

Value	Count	Frequency (%)
95	2	0.4%
94	1	0.2%
92	3	0.6%
91	3	0.6%
90	2	0.4%
89	5	1.1%
88	2	0.4%
87	2	0.4%
86	4	0.9%
85	4	0.9%

BIO_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

0.0	71
4.0	60
3.0	56
5.0	52
3.5	50

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	4.0
3rd row	3.5
4th row	0.0
5th row	3.5

Common Values

Value	Count	Frequency (%)
0.0	71	15.2%
4.0	60	12.8%
3.0	56	12.0%
5.0	52	11.1%
3.5	50	10.7%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	71	24.6%
4.0	60	20.8%
3.0	56	19.4%
5.0	52	18.0%
3.5	50	17.3%

Most occurring characters

Value	Count	Frequency (%)
0	310	35.8%
.	289	33.3%
3	106	12.2%
5	102	11.8%
4	60	6.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	310	53.6%
3	106	18.3%
5	102	17.6%
4	60	10.4%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	310	35.8%
.	289	33.3%
3	106	12.2%
5	102	11.8%
4	60	6.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	310	35.8%
.	289	33.3%
3	106	12.2%
5	102	11.8%
4	60	6.9%

BIO_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	67
A	60
B	56
A+	52
A-	50

Length

Max length	3
Median length	1
Mean length	1.380622837
Min length	1

Characters and Unicode

Total characters	399
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	A
3rd row	A-
4th row	F
5th row	A-

Common Values

Value	Count	Frequency (%)
F	67	14.3%
A	60	12.8%
B	56	12.0%
A+	52	11.1%
A-	50	10.7%
ABS	4	0.9%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	162	56.1%
f	67	23.2%
b	56	19.4%
abs	4	1.4%

Most occurring characters

Value	Count	Frequency (%)
A	166	41.6%
F	67	16.8%
B	60	15.0%
+	52	13.0%
-	50	12.5%
S	4	1.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	297	74.4%
Math Symbol	52	13.0%
Dash Punctuation	50	12.5%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	166	55.9%
F	67	22.6%
B	60	20.2%
S	4	1.3%

Dash Punctuation

Value	Count	Frequency (%)
-	50	100.0%

Math Symbol

Value	Count	Frequency (%)
+	52	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	297	74.4%
Common	102	25.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	166	55.9%
F	67	22.6%
B	60	20.2%
S	4	1.3%

Common

Value	Count	Frequency (%)
+	52	51.0%
-	50	49.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	399	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	166	41.6%
F	67	16.8%
B	60	15.0%
+	52	13.0%
-	50	12.5%
S	4	1.0%

Math_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	82
Distinct (%)	28.4%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	47.16955017

Minimum	5
Maximum	95
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	5
5-th percentile	16
Q1	30
median	49
Q3	64
95-th percentile	82.6
Maximum	95
Range	90
Interquartile range (IQR)	34

Descriptive statistics

Standard deviation	20.79685907
Coefficient of variation (CV)	0.4408958533
Kurtosis	-0.852223021
Mean	47.16955017
Median Absolute Deviation (MAD)	17
Skewness	0.08752390482
Sum	13632
Variance	432.5093474
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
49	12	2.6%
55	8	1.7%
42	7	1.5%
44	7	1.5%
63	7	1.5%
59	7	1.5%
25	6	1.3%
66	6	1.3%
52	6	1.3%
28	6	1.3%
Other values (72)	217	46.4%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	1	0.2%
6	1	0.2%
8	1	0.2%
9	1	0.2%
10	1	0.2%
11	1	0.2%
12	2	0.4%
13	1	0.2%
14	2	0.4%
15	3	0.6%

Value	Count	Frequency (%)
95	1	0.2%
94	1	0.2%
92	1	0.2%
91	1	0.2%
86	4	0.9%
85	4	0.9%
84	1	0.2%
83	2	0.4%
82	2	0.4%
80	4	0.9%

Math_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

0.0	144
3.0	50
3.5	47
4.0	27
5.0	21

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	3.5
3rd row	3.5
4th row	3.0
5th row	4.0

Common Values

Value	Count	Frequency (%)
0.0	144	30.8%
3.0	50	10.7%
3.5	47	10.0%
4.0	27	5.8%
5.0	21	4.5%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	144	49.8%
3.0	50	17.3%
3.5	47	16.3%
4.0	27	9.3%
5.0	21	7.3%

Most occurring characters

Value	Count	Frequency (%)
0	386	44.5%
.	289	33.3%
3	97	11.2%
5	68	7.8%
4	27	3.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	386	66.8%
3	97	16.8%
5	68	11.8%
4	27	4.7%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	386	44.5%
.	289	33.3%
3	97	11.2%
5	68	7.8%
4	27	3.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	386	44.5%
.	289	33.3%
3	97	11.2%
5	68	7.8%
4	27	3.1%

Math_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	121
B	50
A-	47
A	27
ABS	23

Length

Max length	3
Median length	1
Mean length	1.394463668
Min length	1

Characters and Unicode

Total characters	403
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	A-
3rd row	A-
4th row	B
5th row	A

Common Values

Value	Count	Frequency (%)
F	121	25.9%
B	50	10.7%
A-	47	10.0%
A	27	5.8%
ABS	23	4.9%
A+	21	4.5%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	121	41.9%
a	95	32.9%
b	50	17.3%
abs	23	8.0%

Most occurring characters

Value	Count	Frequency (%)
F	121	30.0%
A	118	29.3%
B	73	18.1%
-	47	11.7%
S	23	5.7%
+	21	5.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	335	83.1%
Dash Punctuation	47	11.7%
Math Symbol	21	5.2%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	121	36.1%
A	118	35.2%
B	73	21.8%
S	23	6.9%

Dash Punctuation

Value	Count	Frequency (%)
-	47	100.0%

Math Symbol

Value	Count	Frequency (%)
+	21	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	335	83.1%
Common	68	16.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	121	36.1%
A	118	35.2%
B	73	21.8%
S	23	6.9%

Common

Value	Count	Frequency (%)
-	47	69.1%
+	21	30.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	403	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	121	30.0%
A	118	29.3%
B	73	18.1%
-	47	11.7%
S	23	5.7%
+	21	5.2%

ICT_Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	70
Distinct (%)	24.2%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	64.67820069

Minimum	0
Maximum	96
Zeros	1
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	34
Q1	54
median	66
Q3	78
95-th percentile	90
Maximum	96
Range	96
Interquartile range (IQR)	24

Descriptive statistics

Standard deviation	16.86373829
Coefficient of variation (CV)	0.2607329534
Kurtosis	-0.01730564706
Mean	64.67820069
Median Absolute Deviation (MAD)	12
Skewness	-0.4484742361
Sum	18692
Variance	284.385669
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
66	12	2.6%
67	11	2.4%
84	10	2.1%
63	9	1.9%
72	9	1.9%
62	8	1.7%
74	8	1.7%
61	8	1.7%
80	8	1.7%
54	8	1.7%
Other values (60)	198	42.3%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.2%
22	1	0.2%
26	1	0.2%
29	4	0.9%
30	1	0.2%
31	1	0.2%
32	4	0.9%
33	1	0.2%
34	2	0.4%
35	2	0.4%

Value	Count	Frequency (%)
96	1	0.2%
95	1	0.2%
94	2	0.4%
93	6	1.3%
92	1	0.2%
91	3	0.6%
90	3	0.6%
89	2	0.4%
88	4	0.9%
87	4	0.9%

ICt_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

5.0	68
3.5	66
4.0	58
3.0	51
0.0	46

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	4.0
3rd row	3.5
4th row	0.0
5th row	3.5

Common Values

Value	Count	Frequency (%)
5.0	68	14.5%
3.5	66	14.1%
4.0	58	12.4%
3.0	51	10.9%
0.0	46	9.8%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
5.0	68	23.5%
3.5	66	22.8%
4.0	58	20.1%
3.0	51	17.6%
0.0	46	15.9%

Most occurring characters

Value	Count	Frequency (%)
.	289	33.3%
0	269	31.0%
5	134	15.5%
3	117	13.5%
4	58	6.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	269	46.5%
5	134	23.2%
3	117	20.2%
4	58	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	289	33.3%
0	269	31.0%
5	134	15.5%
3	117	13.5%
4	58	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	289	33.3%
0	269	31.0%
5	134	15.5%
3	117	13.5%
4	58	6.7%

ICT_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	2.1%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

A+	68
A-	66
A	58
B	51
F	42

Length

Max length	3
Median length	1
Mean length	1.491349481
Min length	1

Characters and Unicode

Total characters	431
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	A
3rd row	A-
4th row	F
5th row	A-

Common Values

Value	Count	Frequency (%)
A+	68	14.5%
A-	66	14.1%
A	58	12.4%
B	51	10.9%
F	42	9.0%
ABS	4	0.9%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
a	192	66.4%
b	51	17.6%
f	42	14.5%
abs	4	1.4%

Most occurring characters

Value	Count	Frequency (%)
A	196	45.5%
+	68	15.8%
-	66	15.3%
B	55	12.8%
F	42	9.7%
S	4	0.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	297	68.9%
Math Symbol	68	15.8%
Dash Punctuation	66	15.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	196	66.0%
B	55	18.5%
F	42	14.1%
S	4	1.3%

Dash Punctuation

Value	Count	Frequency (%)
-	66	100.0%

Math Symbol

Value	Count	Frequency (%)
+	68	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	297	68.9%
Common	134	31.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	196	66.0%
B	55	18.5%
F	42	14.1%
S	4	1.3%

Common

Value	Count	Frequency (%)
+	68	50.7%
-	66	49.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	431	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	196	45.5%
+	68	15.8%
-	66	15.3%
B	55	12.8%
F	42	9.7%
S	4	0.9%

APT
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	45
Distinct (%)	16.0%
Missing	186
Missing (%)	39.7%
Infinite	0
Infinite (%)	0.0%
Mean	46.54609929

Minimum	9
Maximum	73
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	9
5-th percentile	32
Q1	40
median	46
Q3	53
95-th percentile	62.95
Maximum	73
Range	64
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.571588427
Coefficient of variation (CV)	0.2056367466
Kurtosis	0.3504232302
Mean	46.54609929
Median Absolute Deviation (MAD)	6
Skewness	0.0174031445
Sum	13126
Variance	91.61530502
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=45)

Value	Count	Frequency (%)
50	21	4.5%
42	19	4.1%
38	17	3.6%
43	14	3.0%
47	13	2.8%
51	13	2.8%
41	11	2.4%
52	10	2.1%
46	9	1.9%
44	9	1.9%
Other values (35)	146	31.2%
(Missing)	186	39.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
9	1	0.2%
24	1	0.2%
27	1	0.2%
28	3	0.6%
29	3	0.6%
30	3	0.6%
31	2	0.4%
32	3	0.6%
33	4	0.9%
34	8	1.7%

Value	Count	Frequency (%)
73	2	0.4%
71	1	0.2%
68	1	0.2%
66	5	1.1%
65	2	0.4%
64	1	0.2%
63	3	0.6%
62	1	0.2%
61	3	0.6%
60	5	1.1%

APT_G.P.
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	1.4%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

0.0	170
3.0	88
3.5	28
4.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	867
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.5
2nd row	3.0
3rd row	3.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	170	36.3%
3.0	88	18.8%
3.5	28	6.0%
4.0	3	0.6%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	170	58.8%
3.0	88	30.4%
3.5	28	9.7%
4.0	3	1.0%

Most occurring characters

Value	Count	Frequency (%)
0	431	49.7%
.	289	33.3%
3	116	13.4%
5	28	3.2%
4	3	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	578	66.7%
Other Punctuation	289	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	431	74.6%
3	116	20.1%
5	28	4.8%
4	3	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	289	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	867	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	431	49.7%
.	289	33.3%
3	116	13.4%
5	28	3.2%
4	3	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	867	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	431	49.7%
.	289	33.3%
3	116	13.4%
5	28	3.2%
4	3	0.3%

APT_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	1.4%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	170
B	88
A-	28
A	3

Length

Max length	2
Median length	1
Mean length	1.096885813
Min length	1

Characters and Unicode

Total characters	317
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A-
2nd row	B
3rd row	B
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	170	36.3%
B	88	18.8%
A-	28	6.0%
A	3	0.6%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	170	58.8%
b	88	30.4%
a	31	10.7%

Most occurring characters

Value	Count	Frequency (%)
F	170	53.6%
B	88	27.8%
A	31	9.8%
-	28	8.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	289	91.2%
Dash Punctuation	28	8.8%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	170	58.8%
B	88	30.4%
A	31	10.7%

Dash Punctuation

Value	Count	Frequency (%)
-	28	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	289	91.2%
Common	28	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	170	58.8%
B	88	30.4%
A	31	10.7%

Common

Value	Count	Frequency (%)
-	28	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	317	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	170	53.6%
B	88	27.8%
A	31	9.8%
-	28	8.8%

Grand Total
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	202
Distinct (%)	69.9%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	364.2456747

Minimum	100
Maximum	585
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	100
5-th percentile	204.8
Q1	299
median	366
Q3	433
95-th percentile	514.2
Maximum	585
Range	485
Interquartile range (IQR)	134

Descriptive statistics

Standard deviation	96.42606655
Coefficient of variation (CV)	0.2647281031
Kurtosis	-0.3209065981
Mean	364.2456747
Median Absolute Deviation (MAD)	67
Skewness	-0.1252499247
Sum	105267
Variance	9297.986309
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
492	5	1.1%
367	4	0.9%
374	4	0.9%
409	4	0.9%
309	4	0.9%
378	4	0.9%
348	3	0.6%
445	3	0.6%
314	3	0.6%
337	3	0.6%
Other values (192)	252	53.8%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100	1	0.2%
128	1	0.2%
136	1	0.2%
137	1	0.2%
145	1	0.2%
148	1	0.2%
155	1	0.2%
173	1	0.2%
174	1	0.2%
180	1	0.2%

Value	Count	Frequency (%)
585	1	0.2%
583	1	0.2%
576	1	0.2%
573	1	0.2%
569	1	0.2%
558	1	0.2%
545	1	0.2%
543	1	0.2%
542	2	0.4%
532	1	0.2%

TTL_GP
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	25
Distinct (%)	8.7%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	1.923321799

Minimum	0
Maximum	5
Zeros	153
Zeros (%)	32.7%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	4
95-th percentile	4.884
Maximum	5
Range	5
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.078068356
Coefficient of variation (CV)	1.080457965
Kurtosis	-1.840702053
Mean	1.923321799
Median Absolute Deviation (MAD)	0
Skewness	0.2169295267
Sum	555.84
Variance	4.318368094
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
0	153	32.7%
5	14	3.0%
4.42	10	2.1%
3.92	10	2.1%
3.5	9	1.9%
4.17	8	1.7%
4.33	7	1.5%
3.25	7	1.5%
3.83	7	1.5%
3.33	7	1.5%
Other values (15)	57	12.2%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	153	32.7%
3	1	0.2%
3.17	3	0.6%
3.25	7	1.5%
3.33	7	1.5%
3.42	2	0.4%
3.5	9	1.9%
3.58	6	1.3%
3.67	3	0.6%
3.75	5	1.1%

Value	Count	Frequency (%)
5	14	3.0%
4.92	1	0.2%
4.83	3	0.6%
4.75	6	1.3%
4.67	3	0.6%
4.58	3	0.6%
4.5	5	1.1%
4.42	10	2.1%
4.33	7	1.5%
4.25	5	1.1%

TTL_L.G.
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	1.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

F	153
A	62
A-	40
B	20
A+	14

Length

Max length	2
Median length	1
Mean length	1.186851211
Min length	1

Characters and Unicode

Total characters	343
Distinct characters	5
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	A
2nd row	A-
3rd row	A-
4th row	F
5th row	F

Common Values

Value	Count	Frequency (%)
F	153	32.7%
A	62	13.2%
A-	40	8.5%
B	20	4.3%
A+	14	3.0%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	153	52.9%
a	116	40.1%
b	20	6.9%

Most occurring characters

Value	Count	Frequency (%)
F	153	44.6%
A	116	33.8%
-	40	11.7%
B	20	5.8%
+	14	4.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	289	84.3%
Dash Punctuation	40	11.7%
Math Symbol	14	4.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
F	153	52.9%
A	116	40.1%
B	20	6.9%

Dash Punctuation

Value	Count	Frequency (%)
-	40	100.0%

Math Symbol

Value	Count	Frequency (%)
+	14	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	289	84.3%
Common	54	15.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
F	153	52.9%
A	116	40.1%
B	20	6.9%

Common

Value	Count	Frequency (%)
-	40	74.1%
+	14	25.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	343	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
F	153	44.6%
A	116	33.8%
-	40	11.7%
B	20	5.8%
+	14	4.1%

No.s of F
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	7
Distinct (%)	2.4%
Missing	179
Missing (%)	38.2%
Infinite	0
Infinite (%)	0.0%
Mean	1.477508651

Minimum	0
Maximum	6
Zeros	136
Zeros (%)	29.1%
Negative	0
Negative (%)	0.0%
Memory size	3.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	3
95-th percentile	5
Maximum	6
Range	6
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.823937863
Coefficient of variation (CV)	1.234468483
Kurtosis	-0.01903999775
Mean	1.477508651
Median Absolute Deviation (MAD)	1
Skewness	1.061424147
Sum	427
Variance	3.326749327
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	136	29.1%
1	43	9.2%
2	34	7.3%
3	30	6.4%
4	17	3.6%
5	16	3.4%
6	13	2.8%
(Missing)	179	38.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	136	29.1%
1	43	9.2%
2	34	7.3%
3	30	6.4%
4	17	3.6%
5	16	3.4%
6	13	2.8%

Value	Count	Frequency (%)
6	13	2.8%
5	16	3.4%
4	17	3.6%
3	30	6.4%
2	34	7.3%
1	43	9.2%
0	136	29.1%

Sec_Position
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	26
Distinct (%)	9.0%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

--	153
1	10
2	10
5	10
3	10
Other values (21)	96

Length

Max length	2
Median length	2
Mean length	1.712802768
Min length	1

Characters and Unicode

Total characters	495
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	1.4%

Sample

1st row	2
2nd row	5
3rd row	4
4th row	--
5th row	--

Common Values

Value	Count	Frequency (%)
--	153	32.7%
1	10	2.1%
2	10	2.1%
5	10	2.1%
3	10	2.1%
7	9	1.9%
4	9	1.9%
6	9	1.9%
10	8	1.7%
9	8	1.7%
Other values (16)	53	11.3%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	153	52.9%
1	10	3.5%
5	10	3.5%
2	10	3.5%
3	10	3.5%
4	9	3.1%
6	9	3.1%
7	9	3.1%
10	8	2.8%
9	8	2.8%
Other values (16)	53	18.3%

Most occurring characters

Value	Count	Frequency (%)
-	306	61.8%
1	63	12.7%
2	26	5.3%
3	15	3.0%
5	14	2.8%
4	14	2.8%
7	12	2.4%
6	12	2.4%
9	11	2.2%
0	11	2.2%

Most occurring categories

Value	Count	Frequency (%)
Dash Punctuation	306	61.8%
Decimal Number	189	38.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	63	33.3%
2	26	13.8%
3	15	7.9%
5	14	7.4%
4	14	7.4%
7	12	6.3%
6	12	6.3%
9	11	5.8%
0	11	5.8%
8	11	5.8%

Dash Punctuation

Value	Count	Frequency (%)
-	306	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	495	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	306	61.8%
1	63	12.7%
2	26	5.3%
3	15	3.0%
5	14	2.8%
4	14	2.8%
7	12	2.4%
6	12	2.4%
9	11	2.2%
0	11	2.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	495	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	306	61.8%
1	63	12.7%
2	26	5.3%
3	15	3.0%
5	14	2.8%
4	14	2.8%
7	12	2.4%
6	12	2.4%
9	11	2.2%
0	11	2.2%

Position
Categorical

HIGH CARDINALITY
MISSING

Distinct	135
Distinct (%)	46.7%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

--	153
6	2
20	2
19	1
21	1
Other values (130)	130

Length

Max length	3
Median length	2
Mean length	2.08650519
Min length	1

Characters and Unicode

Total characters	603
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	132 ?
Unique (%)	45.7%

Sample

1st row	66
2nd row	86
3rd row	80
4th row	--
5th row	--

Common Values

Value	Count	Frequency (%)
--	153	32.7%
6	2	0.4%
20	2	0.4%
19	1	0.2%
21	1	0.2%
130	1	0.2%
112	1	0.2%
2	1	0.2%
77	1	0.2%
96	1	0.2%
Other values (125)	125	26.7%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	153	52.9%
20	2	0.7%
6	2	0.7%
125	1	0.3%
64	1	0.3%
85	1	0.3%
118	1	0.3%
62	1	0.3%
21	1	0.3%
22	1	0.3%
Other values (125)	125	43.3%

Most occurring characters

Value	Count	Frequency (%)
-	306	50.7%
1	69	11.4%
2	35	5.8%
3	29	4.8%
6	24	4.0%
0	24	4.0%
4	24	4.0%
8	23	3.8%
9	23	3.8%
5	23	3.8%

Most occurring categories

Value	Count	Frequency (%)
Dash Punctuation	306	50.7%
Decimal Number	297	49.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	69	23.2%
2	35	11.8%
3	29	9.8%
6	24	8.1%
0	24	8.1%
4	24	8.1%
8	23	7.7%
9	23	7.7%
5	23	7.7%
7	23	7.7%

Dash Punctuation

Value	Count	Frequency (%)
-	306	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	603	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	306	50.7%
1	69	11.4%
2	35	5.8%
3	29	4.8%
6	24	4.0%
0	24	4.0%
4	24	4.0%
8	23	3.8%
9	23	3.8%
5	23	3.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	603	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	306	50.7%
1	69	11.4%
2	35	5.8%
3	29	4.8%
6	24	4.0%
0	24	4.0%
4	24	4.0%
8	23	3.8%
9	23	3.8%
5	23	3.8%

ATP_Position
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	21
Distinct (%)	7.3%
Missing	179
Missing (%)	38.2%
Memory size	3.8 KiB

--	173
20	21
19	13
18	10
17	8
Other values (16)	64

Length

Max length	2
Median length	2
Mean length	1.944636678
Min length	1

Characters and Unicode

Total characters	562
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	2.1%

Sample

1st row	11
2nd row	12
3rd row	19
4th row	--
5th row	--

Common Values

Value	Count	Frequency (%)
--	173	37.0%
20	21	4.5%
19	13	2.8%
18	10	2.1%
17	8	1.7%
15	8	1.7%
10	8	1.7%
16	7	1.5%
12	7	1.5%
11	7	1.5%
Other values (11)	27	5.8%
(Missing)	179	38.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	173	59.9%
20	21	7.3%
19	13	4.5%
18	10	3.5%
15	8	2.8%
17	8	2.8%
10	8	2.8%
12	7	2.4%
11	7	2.4%
16	7	2.4%
Other values (11)	27	9.3%

Most occurring characters

Value	Count	Frequency (%)
-	346	61.6%
1	88	15.7%
2	29	5.2%
0	29	5.2%
9	14	2.5%
8	13	2.3%
4	10	1.8%
5	9	1.6%
7	9	1.6%
6	8	1.4%

Most occurring categories

Value	Count	Frequency (%)
Dash Punctuation	346	61.6%
Decimal Number	216	38.4%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	88	40.7%
2	29	13.4%
0	29	13.4%
9	14	6.5%
8	13	6.0%
4	10	4.6%
5	9	4.2%
7	9	4.2%
6	8	3.7%
3	7	3.2%

Dash Punctuation

Value	Count	Frequency (%)
-	346	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	562	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
-	346	61.6%
1	88	15.7%
2	29	5.2%
0	29	5.2%
9	14	2.5%
8	13	2.3%
4	10	1.8%
5	9	1.6%
7	9	1.6%
6	8	1.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	562	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	346	61.6%
1	88	15.7%
2	29	5.2%
0	29	5.2%
9	14	2.5%
8	13	2.3%
4	10	1.8%
5	9	1.6%
7	9	1.6%
6	8	1.4%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	ID No.	Name English	Section	4th Sub	Ban_Total	Ban_G.P.	Ban_L.G.	Eng_Total	Eng_G.P.	Eng_L.G.	Phy_Total	Phy_G.P.	Phy_L.G.	Che_Total	Che_G.P.	Che_L.G.	BIO_Total	BIO_G.P.	BIO_L.G.	Math_Total	Math_G.P.	Math_L.G.	ICT_Total	ICt_G.P.	ICT_L.G.	APT	APT_G.P.	APT_L.G.	Grand Total	TTL_GP	TTL_L.G.	No.s of F	Sec_Position	Position	ATP_Position
0	2190001.0	SAIMA SHARMIN MONISHA	Shankhamala	Agri	65.0	3.5	A-	61.0	3.5	A-	92.0	5.0	A+	79.0	5.0	A+	68.0	3.5	A-	67.0	3.5	A-	63.0	3.5	A-	59.0	3.5	A-	445.0	4.08	A	0.0	2	66	11
1	2190002.0	MOSSAMAT NUSAIBA ISLAM	Shankhamala	Agri	77.0	4.0	A	57.0	3.0	B	70.0	4.0	A	68.0	3.5	A-	69.0	4.0	A	68.0	3.5	A-	71.0	4.0	A	58.0	3.0	B	430.0	3.83	A-	0.0	5	86	12
2	2190004.0	TAHMINA AFROJ RITU	Shankhamala	Agri	69.0	4.0	A	50.0	3.0	B	79.0	5.0	A+	73.0	4.0	A	66.0	3.5	A-	67.0	3.5	A-	62.0	3.5	A-	51.0	3.0	B	416.0	3.92	A-	0.0	4	80	19
3	2190005.0	ANUPOMA DEBSHARMA	Shankhamala	Agri	53.0	3.0	B	44.0	0.0	F	65.0	3.5	A-	37.0	0.0	F	44.0	0.0	F	56.0	3.0	B	46.0	0.0	F	41.0	0.0	F	295.0	0.00	F	4.0	--	--	--
4	2190007.0	MARIA AKTER MIM	Shankhamala	Agri	63.0	3.5	A-	44.0	0.0	F	84.0	5.0	A+	68.0	3.5	A-	64.0	3.5	A-	71.0	4.0	A	67.0	3.5	A-	47.0	0.0	F	411.0	0.00	F	1.0	--	--	--
5	2190008.0	ZARIN TASNIM	Shankhamala	Agri	71.0	4.0	A	68.0	3.5	A-	75.0	4.0	A	67.0	3.5	A-	66.0	3.5	A-	82.0	5.0	A+	67.0	3.5	A-	59.0	3.5	A-	446.0	4.00	A	0.0	3	69	11
6	2190011.0	MST. SABIHA SULTANA RIMA	Shankhamala	Agri	49.0	3.0	B	42.0	0.0	F	57.0	3.0	B	58.0	3.0	B	47.0	0.0	F	61.0	3.5	A-	36.0	0.0	F	42.0	0.0	F	300.0	0.00	F	3.0	--	--	--
7	2190013.0	MUSFEKA IFFAT SENIN	Shankhamala	Agri	64.0	3.5	A-	50.0	3.0	B	97.0	5.0	A+	80.0	5.0	A+	82.0	5.0	A+	64.0	3.5	A-	78.0	4.0	A	52.0	3.0	B	465.0	4.33	A	0.0	1	48	18
8	2190019.0	ADDOSHI SHIARA RAKHI	Shankhamala	Agri	56.0	3.0	B	49.0	3.0	B	90.0	5.0	A+	63.0	3.5	A-	52.0	3.0	B	58.0	3.0	B	55.0	3.0	B	50.0	3.0	B	373.0	3.42	B	0.0	7	116	20
9	2190020.0	MAHABUBA AKTER OISHI	Shankhamala	Agri	56.0	3.0	B	43.0	0.0	F	94.0	5.0	A+	68.0	3.5	A-	72.0	4.0	A	59.0	3.5	A-	63.0	3.5	A-	73.0	4.0	A	405.0	0.00	F	1.0	--	--	1

Last rows

	ID No.	Name English	Section	4th Sub	Ban_Total	Ban_G.P.	Ban_L.G.	Eng_Total	Eng_G.P.	Eng_L.G.	Phy_Total	Phy_G.P.	Phy_L.G.	Che_Total	Che_G.P.	Che_L.G.	BIO_Total	BIO_G.P.	BIO_L.G.	Math_Total	Math_G.P.	Math_L.G.	ICT_Total	ICt_G.P.	ICT_L.G.	APT	APT_G.P.	APT_L.G.	Grand Total	TTL_GP	TTL_L.G.	No.s of F	Sec_Position	Position	ATP_Position
458	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
459	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
460	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
461	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
462	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
463	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
464	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
465	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
466	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
467	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	ID No.	Name English	Section	4th Sub	Ban_Total	Ban_G.P.	Ban_L.G.	Eng_Total	Eng_G.P.	Eng_L.G.	Phy_Total	Phy_G.P.	Phy_L.G.	Che_Total	Che_G.P.	Che_L.G.	BIO_Total	BIO_G.P.	BIO_L.G.	Math_Total	Math_G.P.	Math_L.G.	ICT_Total	ICt_G.P.	ICT_L.G.	APT	APT_G.P.	APT_L.G.	Grand Total	TTL_GP	TTL_L.G.	No.s of F	Sec_Position	Position	ATP_Position
458	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
459	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
460	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
461	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
462	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
463	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
464	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
465	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
466	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
467	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	ID No.	Name English	Section	4th Sub	Ban_Total	Ban_G.P.	Ban_L.G.	Eng_Total	Eng_G.P.	Eng_L.G.	Phy_Total	Phy_G.P.	Phy_L.G.	Che_Total	Che_G.P.	Che_L.G.	BIO_Total	BIO_G.P.	BIO_L.G.	Math_Total	Math_G.P.	Math_L.G.	ICT_Total	ICt_G.P.	ICT_L.G.	APT	APT_G.P.	APT_L.G.	Grand Total	TTL_GP	TTL_L.G.	No.s of F	Sec_Position	Position	ATP_Position
458	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
459	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
460	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
461	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
462	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
463	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
464	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
465	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
466	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
467	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Space Separator

Other Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Dash Punctuation

Math Symbol

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

	ID No.	Name English	Section	4th Sub	Ban_Total	Ban_G.P.	Ban_L.G.	Eng_Total	Eng_G.P.	Eng_L.G.	Phy_Total	Phy_G.P.	Phy_L.G.	Che_Total	Che_G.P.	Che_L.G.	BIO_Total	BIO_G.P.	BIO_L.G.	Math_Total	Math_G.P.	Math_L.G.	ICT_Total	ICt_G.P.	ICT_L.G.	APT	APT_G.P.	APT_L.G.	Grand Total	TTL_GP	TTL_L.G.	No.s of F	Sec_Position	Position	ATP_Position
458	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
459	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
460	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
461	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
462	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
463	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
464	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
465	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
466	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
467	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN